def _data_dialog(self):
'''
a dialog for data processing
'''
self.progress_processing.setHidden(True)
self.progress_processing.setMinimum(0)
self.progress_processing.setValue(0)
self.tasks = transport.get_result_files(self.work_dir, self.substances)
n_tas = len(self.tasks)
self.solutions = transport.parse_task_dirs(self.work_dir, FNAME_ELEMS)
n_sols = len(self.solutions)
if n_tas - n_sols == 0:
self.button_process_newonly.setHidden(True)
self.button_process_all.setText('Start')
else:
self.button_process_newonly.setVisible(True)
self.button_process_all.setText('All')
msg = "Found {} tasks to analyze. It may take a while\n".format(n_tas)
msg += "{} tasks was already processed (compressed file found), {} still need processing\n".format(
n_sols, n_tas - n_sols)
if self.substances and n_sols > 0:
msg += "\n\nYour task works with multiple substances. Now you close this primary task and open result for single substance in subfolder."
self.label_processing_text.setText(msg)
self.progress_processing.setMaximum(n_tas * 4)
def _analyze_data_selected(self):
'''
action for button_process_newonly
takes only unprocessed tasks in work_dir to process
'''
if not self.tasks:
self.tasks = transport.get_result_files(
self.work_dir, self.substances)
if not self.solutions:
self.solutions = transport.parse_task_dirs(
self.work_dir, FNAME_ELEMS)
dir1 = [path.split(sol)[0] for sol in self.solutions]
dir2 = [path.split(sol)[0] for sol in self.tasks]
unproc_list = [transport.get_result_files(i, self.substances)[0]
for i in dir2 if i not in dir1]
self.messenger('Processing data, it may take a while')
self._analyze_data_routine(unproc_list)
self.messenger('Processing successfully finished', 300)
self._data_dialog()
def __compare_selected_conc(self, elm_list=None):
'''
wrapper for selected method
parses all dirs and sums concentrations for all/selected elements
output a table with sum
'''
sname, filename = self.__get_proper_filename_suma()
master = path.join(self.work_dir, 'master', filename)
mas_conc_suma = transport.load_vysledek(master)
mas_total = concentrations.sum_conc(mas_conc_suma, elm_list)
list_of_conc = []
task_numbers = []
conc = transport.parse_task_dirs(self.work_dir, FNAME_SUMA, sname)
for fname in conc:
conc_suma = transport.load_vysledek(fname)
task_nr = path.split(fname)[0]
task_name = task_nr.split('\\')[-1]
if task_name == 'master':
task_name = '9999999'
task_numbers.append(task_name)
list_of_conc.append(concentrations.sum_conc(conc_suma, elm_list))
grade_vector = concentrations.grade_result(mas_total, list_of_conc)
table_rows = zip(task_numbers, list_of_conc, grade_vector)
table_rows = sorted(
table_rows, key=lambda grade: grade[2], reverse=True)
self.__display_table_rslt(table_rows)
# enable export
self.comparation_table = table_rows
self.button_export_csv.setEnabled(True)
self.spin_grade_filter.setEnabled(True)
self.button_grade_filter.setEnabled(True)
def merge_result_files(self):
'''
Method for merging result files
parses all task dirs, opens result json files and merge values to one big table
discards results in master dir
'''
sname, filename = self.__get_proper_filename_suma()
conc = transport.parse_task_dirs(self.work_dir, FNAME_ELEMS, sname)
merged_table = {}
minval = self.edit_merge_minval.text()
try:
minval = float(minval)
except ValueError:
minval = 0.0
for fname in conc:
elem_conc = transport.load_vysledek(fname)
if not 'master' in fname:
for elid, time_dict in elem_conc.items():
if merged_table.has_key(elid):
merged_table[elid].append(time_dict)
else:
merged_table[elid] = [time_dict, ]
else:
master_conc = elem_conc
output_file = self.work_dir + SEPAR + FNAME_MERGE
self.messenger(
'Merging the results to one file / it may take a while...')
merger.table_to_file(
merged_table, master_conc, output_file, len(conc) - 1, minval)
self.messenger(
'Data has been successfully merged and exported to CSV file')
